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Whole exome sequencing reveals a stop-gain mutation of PKD2 in an autosomal dominant polycystic kidney disease family complicated with aortic dissection

Overview of attention for article published in BMC Medical Genomics, January 2018
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Title
Whole exome sequencing reveals a stop-gain mutation of PKD2 in an autosomal dominant polycystic kidney disease family complicated with aortic dissection
Published in
BMC Medical Genomics, January 2018
DOI 10.1186/s12881-018-0536-6
Pubmed ID
Authors

Wenwen Zhang, Qian Han, Zhao Liu, Wei Zhou, Qing Cao, Weimin Zhou

Abstract

Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder characterized by progressive cyst formation and expansion in the kidneys, which culminates in end-stage renal disease. Aortic dissection is a rare vascular complication of ADPKD and related literature is currently limited. In this report, we described a patient with asymptomatic Stanford B aortic dissection. Further investigation revealed a positive family history of ADPKD and normal renal function. Whole exome sequencing identified a stop-gain mutation c.1774C > T, p.Arg592Ter in the PKD2 gene that segregated in the family. To our knowledge, this is the first report of ADPKD complicated with aortic dissection caused by PKD2 mutation. The case illustrates the importance of aorta imaging and molecular diagnosis in ADPKD patients in order to achieve early recognition of the deadly vascular complication.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 21%
Student > Doctoral Student 2 14%
Lecturer 1 7%
Other 1 7%
Professor 1 7%
Other 3 21%
Unknown 3 21%
Readers by discipline Count As %
Medicine and Dentistry 4 29%
Biochemistry, Genetics and Molecular Biology 3 21%
Computer Science 1 7%
Immunology and Microbiology 1 7%
Neuroscience 1 7%
Other 0 0%
Unknown 4 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 February 2018.
All research outputs
#15,097,241
of 25,382,440 outputs
Outputs from BMC Medical Genomics
#964
of 2,444 outputs
Outputs of similar age
#233,767
of 449,219 outputs
Outputs of similar age from BMC Medical Genomics
#20
of 56 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,444 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 60% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 449,219 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.